The impact of colonial and contemporary land policies on climate change adaptation in Zimbabwe’s communal areas
Bibliographic record
Abstract
The main aim of this article was to examine the impact of colonial and contemporary development policies on climate change adaptation among communal farmers in Zimbabwe. As such, the objective was to document and better understand how the legacy of colonialism, coupled with the current climate change impacts is making adaptation a serious challenge for farmers in particular regions of the country. This study was conducted in Zimbabwe's Buhera Rural District (Ward 30) and Chipinge Rural District (Ward 11). Data collection involved the use of individual household interviews, with the use of a snowball sampling method, focus group discussions, key informant interviews and direct observation in the field. It was found that the lack of income diversity opportunities has further exposed several livelihoods to climate change and compromised their abilities to respond and recover under periods of climatic stress. It was ascertained that the adaptation challenges experienced by African farmers were brought about by the colonial land system that evicted them from their customary lands and allocated them land in poor agroecological regions that fail to support production. The authors argue that climate change adaptation challenges in communal areas should be understood from a colonial and historical development perspective that led to the establishment of communal farming zones. There is also a need to understand climate vulnerability in the context of post-independence development strategies that have led to the underdevelopment of peasant agriculture and reduced farmers' ability to adapt to climate change. Contribution: Climate change adaptation policies should recognise the country's colonial and historical legacy that has led to poverty and other livelihood challenges in communal areas. By acknowledging this, policymakers are better positioned to understand the structural issues making adaptation difficult, and they could intervene by proposing context-specific adaptation strategies that meet the needs of communal farmers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".